The inventive concepts described herein relate to a feature vector classification device and a method thereof.
Feature vector classification may be one of critical factors to determine performance and speed of the recognition technique. A support vector machine (hereinafter, referred to as SVM) may be one of manners used to classify and recognize objects using machinery, and may be widely used thanks to its excellent performance.
However, a larger number of support vectors may be stored through nonlinear kernel to express high complexity using the SVM. Also, complicated operations may be required between input vector and support vector. Much hardware for parallel processing may be required to process the complicated operations in real time. That is, it is difficult to realize embedded system.
The complexity of operations can be simplified by a method of reducing the number of support vectors. With the method, classification performance may be seriously lowered.